The role of intensity standardization in medical image registration

Authors:
Ulaş Bağcı;Jayaram K. Udupa;Li Bai
Affiliations:
School of Computer Science, University of Nottingham, Nottingham NG8 1BB, UK;Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, USA;School of Computer Science, University of Nottingham, Nottingham NG8 1BB, UK
Venue:
Pattern Recognition Letters
Year:
2010

Citing 6
Cited 2

A survey of image registration techniques

ACM Computing Surveys (CSUR)
Interpolation artefacts in mutual information-based image registration

Computer Vision and Image Understanding - Special issue on analysis of volumetric image
Multiresolution Elastic Medical Image Registration in Standard Intensity Scale

SIBGRAPI '07 Proceedings of the XX Brazilian Symposium on Computer Graphics and Image Processing
Generalized scale: Theory, algorithms, and application to image inhomogeneity correction

Computer Vision and Image Understanding
Optimization of mutual information for multiresolution image registration

IEEE Transactions on Image Processing
Projection-based image registration in the presence of fixed-pattern noise

IEEE Transactions on Image Processing

Tissue-based MRI intensity standardization: application to multicentric datasets

Journal of Biomedical Imaging - Special issue on MRI in Neurosciences
Segmentation of female pelvic organs in axial magnetic resonance images using coupled geometric deformable models

Computers in Biology and Medicine

Quantified Score

Hi-index	0.10

Visualization

Abstract

Acquisition-to-acquisition signal intensity variations (non-standardness) are inherent in MR images. Standardization is a post processing method for correcting inter-subject intensity variations through transforming all images from the given image gray scale into a standard gray scale wherein similar intensities achieve similar tissue meanings. The lack of a standard image intensity scale in MRI leads to many difficulties in tissue characterizability, image display, and analysis, including image segmentation. The influence of standardization on these tasks has been documented well; however, effects of standardization on medical image registration have not been studied yet. In this paper, we investigate the role of intensity standardization in registration tasks with systematic and analytic evaluations involving clinical MR images. We conducted nearly 20,000 clinical MR image registration experiments and evaluated the quality of registrations both quantitatively and qualitatively. The evaluations show that intensity variations between images degrades the accuracy of registration performance. The results imply that the accuracy of image registration not only depends on spatial and geometric similarity but also on the similarity of the intensity values for the same tissues in different images.